In the new, connected economy, it has become increasingly important for companies or service providers to become more in tune with their clients and customers. Such contact can be facilitated with automated telephonic transaction systems, in which interactively-selected prompts are played in the context of a telephone transaction, and the replies of a human user are recognized by an automatic speech recognition system.
The answers given by the respondent are processed by the system in order to convert the spoken words to meaning, which can then be utilized interactively, or stored in a database. One example of such a system is described in U.S. Pat. No. 6,990,179, issued in the names of Lucas Merrow et al. on 24 Jan. 2006 and assigned to the assignee of the present application, further discussed below, the entire content of which is incorporated herein by reference.
In order for a computer system to recognize the words that are spoken and convert these words to text, the system must be programmed to phonetically break down the spoken words and convert portions of the words to their textural equivalents. Such a conversion requires an understanding of the components of speech and the formation of the spoken word. The production of speech generates a complex series of rapidly changing acoustic pressure waveforms. These waveforms comprise the basic building blocks of speech, known as phonemes.
Vowels and consonants are phonemes and have many different characteristics, depending on which components of human speech are used. The position of a phoneme in a word has a significant effect on the ultimate sound generated. A spoken word can have several meanings, depending on how it is said. Linguists have identified allophones as acoustic variants of phonemes and use them to more explicitly describe how a particular word is formed.
Automated telephone calls that use speech recognition are a cost effective method of engaging large populations; organizations use this methodology to reach out to thousands of people in a single day.
While such prior art automated telephone call techniques can be effective for their intended purposes, such techniques can present certain problems and limitations. For example, if the telephone calls are perceived by the recipient as being impersonal or context-insensitive, and thus not approximating a conversation with a live human being, the call(s) can be ineffective.